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A National Survey of Musculoskeletal Impairment inRwanda: Prevalence, Causes and Service Implications
Oluwarantimi Atijosan
1
, Dorothea Rischewski
1
, Victoria Simms
1
, Hannah Kuper
1
, BonaventureLinganwa
2
, Assuman Nuhi
2
, Allen Foster
1
, Chris Lavy
1,3
*
1
Department of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom,
2
CBMI, Kigali, Rwanda,
3
NuffieldDepartment of Orthopaedic Surgery, University of Oxford, Oxford, United Kingdom
Abstract
Background:
Accurate information on the prevalence and causes of musculoskeletal impairment (MSI) is lacking in lowincome countries. We present a new survey methodology that is based on sound epidemiological principles and is linked tothe World Health Organisation’s International Classification of Functioning.
Methods:
Clusters were selected with probability proportionate to size. Households were selected within clusters throughcompact segment sampling. 105 clusters of 80 people (all ages) were included. All participants were screened for MSI by aphysiotherapist and medical assistant. Possible cases plus a random sample of 10% of non-MSI cases were examined furtherto ascertain diagnosis, aetiology, quality of life, and treatment needs.
Findings:
6757 of 8368 enumerated individuals (80.8%) were screened. There were 352 cases, giving an overall prevalencefor MSI of 5.2%. (95% CI 4.5–5.9) The prevalence of MSI increased with age and was similar in men and women.Extrapolating these estimates, there are approximately 488,000 MSI diagnoses in Rwanda. Only 8.2% of MSI cases weresevere, while the majority were moderate (43.7%) or mild (46.3%). Diagnostic categories comprised 11.5% congenital, 31.3%trauma, 3.8% infection, 9.0% neurological, and 44.4% non-traumatic non infective acquired. The most common individualdiagnoses were joint disease (13.3%), angular limb deformity (9.7%) and fracture mal- and non-union (7.2%). 96% of all casesrequired further treatment.
Interpretation:
This survey demonstrates a large burden of MSI in Rwanda, which is mostly untreated. The surveymethodology will be useful in other low income countries, to assist with planning services and monitoring trends.
Citation:
Atijosan O, Rischewski D, Simms V, Kuper H, Linganwa B, et al. (2008) A National Survey of Musculoskeletal Impairment in Rwanda: Prevalence, Causesand Service Implications. PLoS ONE 3(7): e2851. doi:10.1371/journal.pone.0002851
Editor:
William Taylor, University of Otago, New Zealand
Received
December 18, 2007;
Accepted
July 2, 2008;
Published
August 6, 2008
Copyright:

2008 Atijosan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the srcinal author and source are credited.
Funding:
CBMI was the main funder of this study, but was not involved in the work or writing of the paper.
Competing Interests:
The authors have declared that no competing interests exist.* E-mail: christopher.lavy@ndos.ox.ac.uk
Introduction
There is a global lack of accurate information on the prevalenceand causes ofphysical disabilityinlow income countries [1,2]. Thereare two main reasons for this deficiency. Firstly, there have not beenmany surveys and secondly there is no universally accepteddefinition of physical disability. The surveys that have beenundertaken have used a variety of definitions of physical disability,and a range of methodologies for measuring disability so thatcomparisons cannot be made between countries [3,4] . For exampleone survey which asked detailed questions about difficulties indifferent aspects of life, showed that Norway had a prevalence of physical disability of 35% while the national census in India, whichmerely asked whether there was a ‘‘physically handicapped’’ personin the household estimated that the prevalence was 0.2% [5]. Withsuch different ways of measuring and defining disability there is littlebenefit in making comparisons between countries, or over timewithin a country. Where there has been a tighter definition of aspecific impairment or symptom such as has been used in theCOPCORD programme (Community-Oriented Program for theControl of Rheumatic Diseases) [6] then it has been possible tostandardise a data collection methodology, with scope for interna-tional comparison. The COPCORD programme is of great value incomparing rheumatic and joint conditions in different countries,however it does not include trauma or non painful congenital oracquired musculoskeletal deformities.The difficulty in defining physical disability stems from its manyanatomical, physiological and pathological presentations andcauses, and its intimate relation to society and the environment.Terminology has also been confusing, and different groups insociety have different reasons for the varied used of the worddisability. This debate is of more than just academic interest as inorder to plan effective services it is important to estimate theprevalence and causes of physical disability, which requires adefinition of the disability being measured and a surveymethodology. There have been many attempts to reach a commonunderstanding of disability, and the World Health Organisation’s(WHO) publication of the International Classification on Func-tioning (ICF) is a major step forward [7]. The ICF classifiesimpairment of body structure and function, and also includesdomains that measure activity and participation in society.
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Rwanda as a country is in the process of rebuilding itsrehabilitation services and facilities for people with musculoskeletalimpairment (MSI) after its genocide and war of 1994 with all thedemographic and structural destruction that took place. In order toplan effective services it is important to estimate the prevalence andcauses of MSI that exist inthe country.The WHO estimatesthat theprevalence of all types of disability on a global level is around 10%[8], but this estimate is of limited use for planning services in specificsituations. Realising this difficulty, Helander developed a ‘RapidCalculation ofDisability Prevalence’ for lessdeveloped regions of theworld and estimated that 4.8% of a population will need somerehabilitation service [9]. Several physical disability surveys havebeen conducted in Rwanda since the 1994 war, but all have theirlimitations. Handicap International carried out a nationwide surveyin 1995 into ‘physical disability’ [10], and found a very lowprevalence of0.58%. Itsown researchers noted that thiswas low andquestioned whether many sections of the population might havebeen inaccessible so soon after the war. A Community BasedRehabilitation project in Kigali carried out a similar survey in 1997and estimated that the prevalence was 1.8% (personal communica-tion), but the sampling methodology was inadequate, and theresearchers believed that many households withheld informationabout family members with physical disabilities.In view of the lack of accurate data on the prevalence andcauses of MSI, we worked with the Ministry of Health of Rwandato develop a survey of MSI of all ages that involved a reliablesampling methodology and a case definition and diagnostic criteriathat could clearly map onto the classification system used in theICF. Our aim was to develop a reliable survey tool that could beused to plan and monitor MSI services in Rwanda and otherdeveloping countries.
Methods
Sample selection – (see also diagram in Appendix S1)
The survey was designed to be nationally representative,including people of all ages. The expected prevalence of MSI inthis group was estimated at approximately 3% [9,11]. Allowing fora required confidence of 95%, a precision of 20%, a populationsize of 8,441,000 in 2005 [11], a design effect of 2.3, and 15% non-response, the required sample size was estimated to be 8399subjects (Epi Info 6.04). In total, 105 clusters of 80 people wereneeded for this survey. A cluster size of 80 people was chosen forlogistical reasons, as it was considered to be the number a teamcould complete in one day. A nationally representative sample of the population wasselected through cluster sampling with probability proportionateto size. A list was produced of all the enumeration areas and theirrespective populations, and a column was created with thecumulative population across the settlements. The total population(i.e. 8,441,000) was divided by the number of clusters required (i.e.105) to derive the sampling interval (i.e. 80,390). The first clusterwas selected by multiplying the sampling interval with a randomnumber between 0 and 1. The resulting number was traced in thecumulative population column and the first cluster was taken fromthe corresponding enumeration area. The following clusters wereidentified by adding the sampling interval to the previous number.Households within clusters were selected through compactsegment sampling [12]. Maps of each selected cluster (i.e.enumeration area) were obtained from the census bureau. Thesemaps included the locations of the head of ten-householdcommunities, thus showing approximate population distribution.The enumeration area was visited two to three days before thesurvey and the village leaders were asked to update the map. Theenumeration area was then divided into segments, so that eachsegment included approximately 80 people. For instance, if anenumeration area comprised 400 people then it would be dividedinto five segments. One of the segments was chosen at random bydrawing lots and all households in the segment were included in thesample sequentially until 80 people were identified. People wereeligible for inclusion if they lived in the household at least threemonths of the year. All the individuals in the final household werescreened, and the number of people needed to complete the clusterwas randomly selected for inclusion (e.g. if the final householdincluded 5 people but only 3 were required to complete the clusterthen 3 out of the 5 were randomly selected for inclusion). If thesegment did not include 80 people then another segment was chosenat random and sampling continued. If an eligible person was absentthe survey team returned to the household to examine him/herbefore leaving the area. If after repeated visits the person could notbe examined, information about his/her presumed MSI status wascollected from relatives or neighbours.
Musculoskeletal impairment assessment
The fieldwork was carried out between October and December,2005. The survey team visited households door-to-door andconducted the MSI screening in the household. The survey teamconsisted of a physiotherapist and an assistant, and they wereassisted in the clusters by a village guide, appointed by the villageleaders. The purpose of the study and the examination procedurewere explained to the subjects and verbal consent was obtainedbefore examination. A standardised protocol was used for the screening andassessment of MSI [13]. A survey record was filled for eacheligible person that included:
N
Demographic information (all participants);
N
A screening examination for MSI (all participants);
N
A standardised interview and examination protocol for MSI(cases and 10% random sample of non-cases)
N
History of MSI (if not examined)
Screening for musculoskeletal impairment
The team physiotherapist screened all participants for MSI byasking them seven questions about difficulties using theirmusculoskeletal system, whether they used a mobility aid, whetherthey felt they had any physical deformity, and how long they hadhad these symptoms. Participants over 5 years of age werequestioned directly, while participants under 5 years were askedthrough proxy, by the child’s main carer. Participants whoanswered ‘‘yes’’ to any of the questions were classified as cases,provided that the condition had lasted for more than one month orwas considered permanent. This screening tool was developed byorthopaedic surgeons together with physiotherapists and has beenshown to have 99% sensitivity and 97% specificity withinterobserver Kappa scores of 0.90 for the diagnostic group [13].
Standardised interview and examination protocol
All cases were examined in more detail by the physiotherapistusing a standardised interview and examination protocol. Arandom 10% sample of non-cases was also examined further, toconfirm their non-case status. The standardised examinationprotocol assessed the aetiology, duration, severity, anatomicallocation, diagnosis, and treatment, both received and required.The standardised interview and examination protocol includedthe following sections:
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a) Physical examinationThe physiotherapist observed the participant as they carried outphysical tasks that required use of the musculoskeletal system (i.e.walking, crouching and upper limb motor skills)b) DiagnosisThe physiotherapist categorized the diagnosis as: congenital,traumatic, infective, neurological, or acquired non traumatic noninfective. Within these categories an algorithm was used to give aspecific diagnosis. Up to two diagnoses were permissible peridentified case of MSI [13].c) Area affected and nature of problemThe physiotherapist recorded information on the area of thebody affected (e.g. arm) and the nature of the problem (e.g.amputation).d) AetiologyWhere this was known it was recorded. It was determined byquestioning the case about when the impairment developed andhow it came about. The physiotherapists were trained as to whatquestions to ask for each aetiology available, which included roadtraffic accidents, war, infection, and familial.e) SeveritySeverity was determined using ICF parameters for the amountof function which has been lost through the presence of the MSI.This was classified as ‘‘mild’’, ‘‘moderate’’ or ‘‘severe’’ [6].f) EQ-5DGeneric quality of life was measured using the EQ-5D scale,which is a public domain health-related quality of life question-naire [14]. This was translated and back translated from Englishinto Kinyarwandan by two medical translators, independently of each other. However, because of time restrictions, this was carriedout independently from the Euroqol group, and the translated version of EQ-5D used in this study has therefore
not
beenapproved by the Euroqol groupg) Treatment givenCurrent treatment received by the participant (if any) wasrecorded.h) Barriers to treatmentCases were asked an open-ended question about why they hadnot accessed treatment for their MSI. Up to four responses wererecorded per case on pre-coded forms.i) Treatment neededTreatment needed was assessed by the physiotherapist accord-ing to standard protocols, appropriate for Rwanda.
Training and quality control
There were three teams, each consisted of a physiotherapist amedical assistant, a village guide and a driver. The teams receivedthree weeks of training. Inter-observer agreement for casedefinition, diagnosis, severity classification and treatment requiredwas assessed between the teams to ensure that it was of anacceptable standard (i.e. kappa
$
0.60). A pilot survey wasundertaken of 480 people in 9 clusters (6 rural and 3 urban) toassess examination process and procedures. During the mainsurvey, teams were accompanied by a field supervisor at least oneday per week, to ensure that a high quality was maintained. Eachday the supervisors checked items of all completed forms in thefield.
Statistical analysis
A database was constructed for data entry using EpiData 3.1.The data were double-entered and validated, and inconsistencieswere checked. Stata 9.0 was used for analysis. The prevalence andcauses of MSI was estimated, taking into account the design effect(DEFF) when estimating the confidence intervals. (see appendix S1for details of estimation of DEFF)
Ethical approval
Ethical approval for this survey was granted by the IndependentEthics Committee in Rwanda and the London School of Hygiene& Tropical Medicine. Permission to proceed was granted by thegovernment, and consent was granted for each cluster visited fromthe community leader at the province, district, sector and cell level.Informed verbal consent was obtained from the subjects afterexplanation of the nature and possible consequences of the study.Written consent was obtained for any photographs that weretaken. All people with treatable MSI were referred to a centralcommunity rehabilitation centre where clinical members of thestudy team reviewed and referred the participants for furthertreatment, as appropriate. The research followed the tenets of theDeclaration of Helsinki.
Role of funding source.The funding for this study was provided by CBM international. One of the authors (OR) was supported by Cure International. The funding organisations played no part in, and had no influence on the design of the study, or the data,collection, analysis or interpretation.
Results
Sampled population (table 1)
A total of 8368 individuals were enumerated and 6757 werescreened (Response rate=80.8%), 1596 (19.1%) were absent, 10(0.1%) refused and 5(0.1%) were unable to communicate. Theresponse rate was higher in women (84.8%) than in men (76.3%). Among the participants that were enumerated but not examined,88 were believed to have MSI (5.5%). The age- and gender-distribution of the sampled population was very similar to that of the national population (Table 1).
Prevalence of MSI
Of the 6757 individuals screened there were 352 cases of MSIgiving an overall prevalence of MSI of 5.2% (CI 4.5–5.9) (Table 2).The prevalence of MSI fell after early childhood and thenincreased rapidly with age so that it was almost nine-fold higher inpeople aged over 60 years compared to those aged 0–5 years(OR=8.9, 6.0–13.4). The prevalence of MSI was similar in men(5.1%) and women (5.3%). People in rural areas were more likelyto have an MSI (5.4%) than urban dwellers (4.1%), while thosewithout formal education were more likely to have an MSI (5.6%)than those with formal education (4.5%), although theseassociations disappeared after adjustment for age and gender.
Prevalence of MSI by Severity and Gender
The majority of cases of MSI were mild (47.1%) or moderate(44.5%), and few were severe (8.4%) (Table 3). This pattern was very similar in men and women.
MSI Diagnoses
There were a total of 390 diagnoses for 352 people with MSI(Table 4). The most common causes of MSI were joint problems(13.3% of MSI diagnoses), other acquired (12.3%), fracture non ormalunion (7.2%) and other chronic joint injury (6.2%). Overall 44%of MSI were due to acquired non-traumatic non-infective causes,31% due to trauma, 9% neurological were in srcin, 4% due toinfection and 12% congenital. Extrapolating these estimates to thetotal population of Rwanda there were 488,000 MSI diagnoses.With increasing age, the prevalence of MSI increased rapidly(Figure 1). The greatest proportional increase was in MSI diagnoses
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related to trauma and acquired non-traumatic non-infective.Congenital diagnoses were relatively more common in the youngestage group than in older people and the proportion of neurologicaldiagnoses remained relatively constant with increasing age.
Aetiology of MSI
The aetiology of almost one third (32.1%) of the cases wasunknown. A further 28.1% were due to trauma, 15.1% due toinfection, 11.4% due to family history. Other aetiologies, including
Table 1. Age and gender composition of national* and screened sample population.
AgeGroups Male Female Total49.7% 47% 44.3% 50.3% 52% 55.7%National (%)EnumeratedSampleScreenedSample (%) National (%)EnumeratedSampleS Screenedample (%) National (%)EnumeratedSampleScreenedSample (%)0–10
1 302 000 (31.1) 1394 (35.4) 1222 (40.7) 1 287 000 (30.3) 1420 (32.1) 1295 (34.5) 2 589 000 (30.7) 2816 (33.7)
2519 (37.3)11–20
964 000 (23.0) 1029 (26.2) 723 (24.1) 964 000 (22.7) 1081 (24.4) 832 (22.2) 1 929 000 (22.9) 2116 (25.3)
1559 (23.1)21–30
807 000 (19.2) 601 (15.3) 386 (12.9) 808 000 (19.0) 724 (16.4) 567 (15.1) 1 616 000(19.1) 1325 (15.8)
953 (14.1)31–40
482 000 (11.5) 335 (8.5) 234 (7.8) 467 000 (11.0) 422 (9.5) 358 (9.5) 949 000 (11.2) 757 (9.1)
592 (8.8)41–50
326 000(7.7) 275 (7.0) 195 (6.5) 327 000 (7.7) 330 (7.5) 292 (7.8) 654 000 (7.7) 605 (7.2)
487 (7.2)51–60
182 000(4.3) 160 (4.1) 126 (4.2) 205 000 (4.8) 231 (5.2) 203 (5.4) 387 000 (4.6) 392 (4.69)
329 (4.9)
.
60
129 000 (3.1) 140 (3.6) 114 (3.8) 190 000 (4.5) 216 (4.9) 204 (5.4) 289 000 (3.4) 356 (4.3)
318 (4.7)Total 4 193 000(100.0)3934 (100.0) 3000 (100.0) 4 248 000(100.0)4424 (100.0) 3751 (100.0) 8 441 000(100.0)8367 (100.0) 6757
$
(100.0)
*
based on us census bureau data for Rwanda population 2005 as this has age group divisions
$
missing gender data for 6 individualsdoi:10.1371/journal.pone.0002851.t001
Table 2. Prevalence of MSI by age, gender, location and educational level of head of household.
Categories
*
total noscreened.No of MSI casesin that groupPrevalence of MSI(95% CI)Age and sex adjustedOdds Ratios (95%CI)Total 6757 352 5.2% (4.5–5.9%)Age groups
0–5 years 1520 52 3.4% (2.3–4.5%) 16–16 years 2006 39 1.9% (1.2–2.7%) 0.6 ( 0.4–0.9)17–60 years 2913 185 6.4% (5.3–7.4%) 1.9 (1.4–2.7)
.
60 years 318 76 23.9% (18.5–29.3%) 8.9 (6.0–13.4)
Gender
Male 3000 153 5.1% (4.3–6.0%) 1Female 3751 199 5.3% (4.5–6.2%) 0.9 (0.8–1.2)
Location
Rural 5806 312 5.4% (4.6–6.1%) 1Urban 938 39 4.1% (2.7–5.6%) 0.9 (0.6–1.4)
Educational Level of Head of household
No formal education 4346 244 5.6% (4.8–6.5%) 1Formal education 2399 108 4.5% (3.5–5.5%) 0.9 (0.7–1.2)
*
There were some missing valuesdoi:10.1371/journal.pone.0002851.t002
Table 3. Distribution of MSI according to severity and gender, and its association with quality of life.
Male Female TotalMSI status NumberProportion of MSI cases NumberProportion of MSI cases NumberProportion of MSI casesEQ-5D VAS Score(95% CI)
Mild MSI 69 46.0% 94 48.0% 163 47.1% 44.4 (40.5–47.8)Moderate MSI 65 43.3% 89 45.4% 154 44.5% 37.7.(35.4–40.0)Severe MSI 16 10.7% 13 6.6% 29 8.4% 16.9 (11.7–22.0)No MSI 2847 3552 6399 63.1 (61.4–64.7)doi:10.1371/journal.pone.0002851.t003
Rwanda Musculoskeletal SurveyPLoS ONE | www.plosone.org 4 August 2008 | Volume 3 | Issue 7 | e2851
congenital without family history (5.4%), iatrogenic (1.7%), andperinatal hypoxia (0.3%) were relatively rare.
Quality of life
The mean quality of life score was significantly higher in peoplewithout MSI (63.1, 95%CI 61.4–64.7) than among the cases (37.7,35.4–40.0, p value
,
0.001. Severe cases had significantly poorerquality of life (16.9, 11.7–22.0) than moderate (34.9, 31.8–38.0),and mild cases (44.0, 40.5–47.8) (p-value 0.003).
Treatment needed
In total, 641 treatments were needed for the 390 diagnoses(table 5). The most common treatments needed were physicaltherapy (44.5%), surgery (22.9%) or medication (16.1%). Extrap-
Table 4. Cause of MSI in survey, and extrapolated to population of Rwanda.
Diagnosis Number Total in category (%)Extrapolated number of that diagnosticcategory in Rwanda to nearest 1000 (95%CI)A Congenital deformity
45 (12%) 59,000 (95% CI 39,000–74,000)Polydactyly 16Syndactyly 2Other upper limb deformity 4Club foot 4Other lower limb deformity 12Spine deformity 1Cleft lip or cleft palate 2Multiple abnormalities 2Other congenital deformity 2
B Trauma
122 (31%) 156,000 (95% CI 125,000–187,000)Fracture non or malunion 28Burn contracture 4Spine injury 3Head injury 3Joint chronic dislocation 6Other chronic joint injury 24Tendon, muscle or nerve injury 12Amputation 20Other traumatic MSI 22
C Infective
15 (4%) 20,000 (95% CI 9,000–29,000)Joint infection 4Bone infection limb 8Bone infection spine 1Skin/soft tissue infection/wound 2
D Neurological
35 (9%) 44,000 (95% CI 27,000–60,000)Polio 8Para/quadri/tetraplegia 11Cerebral palsy or developmental delay 5Peripheral nerve palsy 4Other neurological MSI 7
E Other acquired non-traumatic non-infective
173 (44%) 216,000 (95% CI 182,000–245,000)Joint problem 52Angular limb deformity 38Skin/soft tissue tumour/swelling 12Spine deformity 2Spine pain 11Limb pain 5Limb swelling 5Other acquired 48TOTAL 390 488,000doi:10.1371/journal.pone.0002851.t004
Rwanda Musculoskeletal SurveyPLoS ONE | www.plosone.org 5 August 2008 | Volume 3 | Issue 7 | e2851

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